According to “State of Retailing Online 2007” (Forrest Research), online shopping, excluding travel, has become a $175 billion phenomenon in the United States as of this writing in mid 2007. This large volume of traffic has spawned numerous inventions, but none that adequately address retailing and purchasing of bundles.
Among other things, there are continuing needs for more effective: (I) pricing and auctioning a bundle of items to be purchased; (II) user interfaces that deliver an integrated shopping experience; and (III) methods for group buying.
(I) Pricing and Auctioning a Bundle of Items to be Purchased
Consider a buyer interested in purchasing a bundle of items (interchangeably called a “package of items”, or simply “multiple items” as used herein), from at least one seller. It is preferred that a “pricing” is done by software, so that a “feasible purchasing solution” is presented to the buyer. One example of such bundles is travel “Custom Packages” offered by Orbitz, packaging hotel stays and flight tickets.
This pricing step addresses a combinatorial optimization problem, which is called “bin packing pricing with an approximate membership” as described herein. Once pricing of a bundle is done, at least one item in the bundle could be auctioned to a number of sellers, and the one offering the lowest price wins the auction.
There are a number of patents on combinatorial auctioning methods, which can be helpful in solving the “bin packing pricing with an approximate membership”. U.S. Pat. No. 7,188,080, Systems and methods wherein a buyer purchases products in a plurality of product categories, Walker, et al., Mar. 6, 2007, claims “facilitating a transaction, comprising: receiving, from a buyer, an indication of a plurality of product categories, each product category being associated with a plurality of products”. U.S. Pat. No. 6,035,288, Solomon, Mar. 7, 2000, Interactive computer-implemented system and method for negotiating sale of goods and/or services, claims an “engine which utilizes said merchant character data and said data inputted by a customer to generate responses to said data inputted by said customer according to said behavioral attributes”. U.S. Pat. No. 5,905,975, Computer implemented methods and apparatus for auctions, Ausubel, May 18, 1999, claims a method for conducting online auctions; and there have been 101 patents that have cited this patent. Other patents include the following: U.S. Pat. No. 7,133,841, Method and computer system for conducting a progressive, price-driven combinatorial auction. U.S. Pat. No. 7,010,505, Method of selecting one or more bids in a combinatorial auction. U.S. Pat. No. 7,043,446, Method for determining the set of winning bids in a combinatorial auction. U.S. Pat. No. 6,272,473, Method, apparatus, and embodied data structures for optimal anytime winner determination in combinatorial auction-type problems.
Combinatorial methods have also been addressed outside the patent literature. The relevant academic literature, for example, includes Rothkopf et al., DIMACS Technical Report 95-09, Computationally Manageable Combinatorial Auctions. In addition, CombineNet, uGenie.com and CampusBooks.com feature pricing bundles (with no auctioning involved). Those systems, however, treat bundles as sets of discrete items, thereby reducing the optimization problem to a form that is too simplistic to capture good deals for shoppers.
In addition, the prior art fails to address the following desirable characteristics:                a. invariant elements, in which bundles can be fixes with respect to one or more of the bundle members;        b. conclusion at will, in which an auction can terminate at any iteration, due to the “invariant” property;        c. non-monotonic price changes, in which the total price typically goes down, but is not guaranteed to go down;        d. substituted bundles, in which an item might be removed, temporarily or permanently, from the bundle; a new item might be added into the bundle; a new bundle of items might be added, whose price might have been fixed;        e. handling of soft commitments, in which buyers need not commit to purchasing any items until the final sale;        f. suggestive biddings for sellers;        g. ability to execute previously stored bidding algorithms for buyers and/or sellers;        h. multiple means of interacting with bidding activities of sellers, in which bidding by sellers could be conducted by software of sellers, or by humans working for sellers; and        i. methods of providing differing degrees of information to auction participants, possibly depending on financial incentives provided by potential participants.        
(II) User Interface that Delivers an Integrated Shopping Experience
Consider a shopper who starts with an “idea” of buying a digital camera as a gift for a 10 year old girl. The shopper begins the search online, and after searching for desired characteristics, decides on a brand and model number. She then goes on a comparison shopping site (e.g., Shopzilla.com), types in the model number, and gets a listing of prices from multiple vendors.
The process is typically arduous, possibly requiring hours of work, investigation of a diversity of online sites, and at the conclusion of the exercise, the outcome is not always the best combination of price, delivery schedule and so forth for the shopper. Moreover, the complexity grows exponentially if the shopper is trying to secure the best overall prices on a bundle of goods.
Thus, there is a clear and present need for a tool that puts a structure into everyday online shopping activities. There is also a need for a user interface that's not too complicated to navigate (therefore not too hard to build and has a fast response time), and serves the need of researching, assembling, and pricing the most popular bundles.
These issues can be readily appreciated with examples of existing shopping websites. Some of the prior art from web sites, mostly comparison shopping sites, are listed in an article on Forbes magazine's web site: http://www.forbes.com/bow/b2c/category.jhtml?id=100. This and all other extrinsic materials discussed herein are incorporated by reference in their entirety. Where a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies and the definition of that term in the reference does not apply.
In CNet's comparison shopping site, for example, a search for a digital camera will show, in the upper part of the page under the title “Select filters to refine your results”, four columns of suggestions: “Find by Price”, “Find by Resolution”, “Find by Manufacturer”, or “Find by” other criteria (see http://shopper.cnet.com/4144-5—9-0.html?query=digital+camera&tag=srch&search Type=sh). Significantly, the number of choices drops as the search gets more specific.
AOL's comparison shopping site is similar (see http://shopping.aol.com/instore/search?op=search&k=digital+camera&rid=4112&id=9&view=list&sbox=1&refCode=aolpartner_shop search&attr=vendors,PAN&attr=popup1,10:975&sbox=1). A panel box for “Shorten your results” is present, with 6 pull-down menus for “Manufacturer”, “MegaPixels”, “Optical Zoom”, “Camera/Lens Type”, “Memory Type”, and “LCD Screen Size”. The design is reminiscent of a typical interface to searching a database, in which attribute-value pairs are filled.
The shopping site Become.com is again similar (see http://www.become.com/shop?q=digital+camera&dcid=7&v=grid&pcolor=−1&scolor=−1&fltr_price=16000%2C98000&min_pric e=&max_price=&fltr_brand=canon&fltr_category=cameraphoto%20&fltr_category=cameraphot o&fltr_category=cameraphoto). There, a search for “digital camera” can be narrowed by the following: “find by color”, “find by brand”, “find by store”, “find by category”, “find by flash functions”, and “find by focus type”, each of which has a list of clickable items.
One problem that is not addressed at all by the various prior art sites is distinguishing between major and minor items. For example, when shopping for a “major item” such as a digital camera, a shopper might want to also purchase a carrying case or an extra battery. None of the existing sites allow a shopper to fix on a particular major item, while allowing variation in the minor items of a bundle.
The closest that the prior art delivers in this respect are customizations of a given item. For example, at the “Configuration interface” at Dell.com, a buyer can customize a particular computer model by selecting a specification for “Processor”, “Operating System”, “LCD Panel”, “Memory”, “Hard Drive”, “Optical Drive”, “Video Card”, and “Sound Option”. The interface offers a “LIST VIEW” and an “ICON VIEW” (see http://configure.us.dell.com/dellstore/config.aspx?c=us&cs=19&1=en&oc=DNCWHG1&s=dhs).
Similarly, at WalMart.com, a shopper can select a digital camera, and then “Accessories to Buy” (five items to click on), or “Similar Items”, in this particular case, an Olympus Digital Camera and a Polaroid P310 Photo Printer (see http://www.walmart.com/catalog/product.do?cpncode=08-25164850-2&dest=9999999997&product_id=5359049&sourceid=15000000000000031291 60&srccode=cii—9324560).
The experience at TriStateCamera.com is also similar. With a selected digital camera model, two “KIT SPECIALS” are presented. Also, to the right of the page, about a dozen “Recommended Accessories” can be clicked on (see http://www.tristatecamera.com/lookat.php?refid=7&sku=OLYSTY710).
Shopping for kits at BuyDig.com or mWave.com is again similar. With a particular digital camera, on BuyDig.com's web site some point in early 2007, five kits are listed under the tab “Money Saving Packages”. This is a very common way for online stores to offer kits. For one thing, such pre-packaged kits do not allow users to pick-and-choose items of interest. For another thing, such pre-packaged kits make apples-to-apples comparisons difficult (see http://www.buydig.com/shop/product.aspx?omid=118&utm_id=14&ref=nextag&utm_source=NexTag&utm_medium=cpc&utm_campaign=OMST710&sku=OMST710). At mWave.com, once a digital camera is chosen, next to the “BUY” button, there are four pull down menus for choosing accessories (see http://www.mwave.com/mwave/skusearch.hm×?SCriteria=3000637&CartID=done&nextloc=).
BlueNile.com focuses on selling diamonds, rings and other jewelry, and has a wonderful interface. On its “search” page, a user can specify “search criteria”, which include cut, carat, clarity, color, among others. Criteria are typically parameterized by sliders. When a user moves a slider, search results change accordingly. Further, search criteria can be changed with the “add/move search criteria” interface. But even there the interface does nothing to help a shopper find the best price for a basket of goods (see http://www.bluenile.com/diamond_search.asp? track=dss&filter_id=0).
(III) There is a Need for an Effective Method for Group Buying
It is not unusual for at least two buyers to aggregate their purchase demands, and make joint commitments to the same purchasing solution. This phenomenon is typically called “group buying”.
There are a number of works in group buying, some of which are listed below. U.S. Pat. No. 6,584,451, Shoham, et al., Jun. 24, 2003, Facilitator for aggregating buyer power in an on-line market system. U.S. Pat. No. 7,146,330, Alon, et al., Dec. 5, 2006, Method and system for creating and managing groups for increasing buying power on the world wide web. U.S. Pat. No. 7,076,447, Peyser, et al., Jul. 11, 2006, Systems and methods for aggregating buyers for the purchase of telecommunication services via a network.
Further, circa late 1990s and early 2000s, there was a number of group buying sites, such as Mercata, Accompany (later changed its name to MobShop), actBIG, ZWirl, and C-Tribe. A description of how such sites work can be found at the following web page http://www.epinions.com/webs-review-7751-ABE9F9F-3964F27D-prod 1.
The general concept of group buying is that groups of members get together in ‘blocs’ to buy a product, bringing the price down. Any member can organize a ‘bloc’, and organizers can be rewarded with a commission on the sale. In the case of ActBig, for example, organizers can secure half of the commission on the sale, which is usually 5%. Members can also post messages to see if other members are interested in a product before they organize a bloc. These three basic functions of the site are separated into three areas: ‘BigDeals’ (buying), ‘BigIdeas’ (organizing blocs), and ‘BigTalk’ (messaging). This makes navigating the site very easy. Functioning blocs and the message boards are then further divided into categories according to the type of product being purchased or discussed.”
The group buying situation is effectively a reverse auction, where at least one shopper posts something to be bid by at least one seller, among which the one who offers the lowest price wins the bid. Compared to time-test auctions on eBay, there are two practical difficulties with reverse auction, and its concatenation with group buying: First is the difficulty of securing commitments from multiple shoppers. Shoppers are often “soft” or fickle in their commitments, and tend to be lured away by outside sellers offering similar deals. Second is the decision of the sellers to reveal pricing information, which is dependent on the shoppers' changing commitments.
Therefore, various commitment schemes, many if not all of which have already been tried by businesses, are either too soft, which makes life hard on a seller; or too hard, which makes life harder on a shopper.
What is needed is a group buying method that is effective in letting a seller and a group of buyers agree on a price, without being hindered by the fickleness of buyers' commitments as seen in practice, or by sellers' reluctance in revealing too much pricing information.
This techniques disclosed herein address a sweet spot for market-making from an informational point of view. Namely, the method facilitates a (spontaneous) group of shoppers and a seller to meet at a price, while striking a balance between sellers' revealing price information and shoppers' commitments. The disclosed subject matter provides a method by which sellers need reveal only necessary price information; the subject matter also allows for shoppers to form groups in which they are free from commitments to each other and to potential sellers.